Databricks Data Engineer

Data Engineer


Job Summary


The Data Engineer builds and supports the pipelines that keep data moving into and through the lakehouse. This is a delivery focused role for engineers who write clean, tested code, work well inside an established architecture, and take ownership of the pipelines they ship. It suits engineers who are strong on fundamentals and ready to grow their Databricks depth on real production workloads.


Key Responsibilities

• Develop, test, and deploy ingestion and transformation pipelines using Python, SQL, and Spark

• Onboard new source systems including databases, files, APIs, and event streams

• Implement data quality checks and monitoring on the pipelines you own

• Build and schedule jobs in Databricks Workflows and troubleshoot failures through to root cause

• Document pipeline logic, dependencies, and operational runbooks

• Support downstream analytics and reporting teams as a partner rather than a ticket queue

• Participate in code review and follow established engineering standards

Required Skills

• 3+ years in data engineering or a closely related engineering role

• Strong SQL and working Python, including experience with PySpark

• Hands on experience building pipelines in a cloud data platform

• Understanding of ELT patterns, incremental loads, and dimensional concepts

• Familiarity with Git and collaborative development practice

• Clear written communication and comfort asking questions early

Preferred Skills

• Databricks Certified Data Engineer Associate

• Experience with Delta Lake, Auto Loader, or Unity Catalog

• Exposure to orchestration tools such as Airflow, ADF, or Databricks Workflows

• Experience working alongside analytics or data science teams

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